Impact of Clinical Decision Support System Assisted prevention and management for Delirium on guideline adherence and cognitive load among Intensive Care Unit nurses (CDSSD-ICU): Protocol of a multicentre, cluster randomized trial

Background Adherence to the delirium bundle intervention is sub-optimal in routine practice, and inappropriate use of the instructional design of interventions may result in higher cognitive load among nurses. It remains unclear whether the Clinical Decision Support System (CDSS) Assisted Prevention and Management for Delirium (CDSS-AntiDelirium) results in the improvement of adherence to delirium intervention and the reduction of extraneous cognitive load, as well as improving adherence to delirium intervention, among nurses in the intensive care unit (ICU). Methods This study (named the CDSSD-ICU) is a multicentre, prospective, cluster randomized controlled clinical trial. A total of six ICUs in two hospitals will be randomized in a 1:1 ratio to receive either the CDSS-AntiDelirium group or the delirium guidelines group. The CDSS-AntiDelirium consists of four modules: delirium assessment tools, risk factor assessment, a nursing care plan, and a nursing checklist module. Each day, nurses will assess ICU patients with the assistance of the CDSS-AntiDelirium. A total of 78 ICU nurses are needed to ensure statistical power. Outcome assessments will be conducted by investigators who are blinded to group assignments. The primary endpoint will be adherence to delirium intervention, the secondary endpoint will be nurses’ cognitive load measured using an instrument to assess different types of cognitive load. Repeated measures analysis of variance will be used to detect group differences. A structural equation model will be used to clarify the mechanism of improvement in adherence. Discussion Although the CDSS has been widely used in hospitals for disease assessment, management, and recording, the applications thereof in the area of delirium are still in infancy. This study could provide scientific evidence regarding the impact of a CDSS on nurses’ adherence and cognitive load and promote its further development in future studies. Clinical trial registration ChiCTR1900023711 (Chinese Clinical Trial Registry).


Background
Cognitive load refers to the total amount of cognitive resources that a person needs to process cognitive activities 1 , and is composed of three different types: intrinsic CL, extraneous CL and germane CL 2,3 .Higher CL, which exceeds one's working memory resource capacity, has been identified as one of the most important problems in providing intensive care 4,5 .It negatively impacts nurses and their patients 4 , which can lead to irritability, memory impairments and mental fatigue of nurses 6,7 , is detrimental to performance of activities, reduced learning capacity for acquiring knowledge 8,9 , and also results in poor patient outcomes and compromises patient safety 6 .The more complicated are the activities performed by nurses, the higher the CL are required, which will hinder the adherence to implement nursing activities 10,11 .
Nursing care in intensive care units (ICU) is characterized by extremely demanding caseloads, performance of complicated activities and making complex decisions 4 .One example is the complex care required in ICU delirium prevention and management interventions.ICU delirium is a common complication of ICU patients with an high incidence of 70% to 87% 12,13 , and associated with longer hospital length of stay (LOS) and increased mortality [13][14][15] .Therefore, the Clinical Practice Guidelines for the Prevention and Management of Pain, Agitation/Sedation, Delirium, Immobility, and Sleep Disruption in Adult Patients in the ICU (PADIS guideline) recommend use of the ABCDEF bundle as a way to prevent and manage ICU delirium [16][17][18] , which focuses on eliminating ICU delirium risk factors [18][19][20] .However, adherence to the ABCDEF bundle is sub-optimal in routine clinical care 21,22 .Previous studies have demonstrated that various barriers may hinder the adherence to implement the bundle, such as heavy workload on nursing care records 23 , complexity algorithm of assessment tools 24,25 , struggle to collect and remember numerous risk factors through multiple channels 26 , lack of knowledge about ICU delirium 27 .Working on complicated activities results in lowered speed for receiving and processing information, decreased capacity of working memory and requires higher cognitive load (CL) 28,29 .
Considering the negative consequence of high CL from delirium care, it is important to provide ICU nurses with the aid of a tool that can reduce CL of nursing care in ICU delirium.With the rapid development of information technology, clinical decision support system (CDSS) has been widely used in most hospitals in worldwide for disease assessment, management and record 11,[30][31][32] .The CDSS play an important role in clinical nursing care, and also commonly used in cognitive psychology 33,34 .It can collect, sort, classify and establish logical relationship of the patient information, and also make use of alert, information feedback to provide decision support during disease diagnosis, treatment and nursing activities 35,36 .Several studies have shown that CDSS can help medical staff to recall less clinical information, which lead to a significant reduction in CL and improvement the adherence to implement nursing interventions 37,38 .
Therefore, we developed an Artificial Intelligence Assisted Prevention and Management for Delirium (AI-AntiDelirium) which including ABCDEF bundle intervention, risk factors and assessment tools of ICU delirium.The aims of this study are to assess the effectiveness of AI-AntiDelirium on adherence and cognitive load of ICU nurses, as well as clinical outcomes related to ICU delirium.

Methods
The protocol is developed according to the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) 39 .

Study design and setting
The AI-AntiDelirium to improve adherence to delirium intervention of ICU nurses is a multicenter, cluster randomized controlled trial (RCT), six ICUs with higher incidence of ICU delirium in two tertiary hospitals are selected, which represent three informatization.The study will be conducted during the period 2022 -2023.Figure 1 shows the design of the study.Nurses who were on study programs outside the hospitals or on leave for various reasons during the study period were excluded.

Intervention Groups
Prior to the study, an educational program is delivered by researchers, including knowledge regarding ICU delirium risk factors, assessment tools (Confusion Assessment Method for the Intensive Care Unit [CAM-ICU], Intensive Care Delirium Screening Checklist [ICDSC]), and ABCDEF bundle interventions.Except that, eligible ICU nurses are trained with how to operate the AI-AntiDelirium.We developed the AI-AntiDelirium, which included the four main modules: ICU delirium assessment module (Figure 1A), risk factors assessment module (Figure 1B), nursing care plan module (Figure 1C) and nursing checklist module (Figure 1D).

Participant timeline
Enrollment and data collection started in November 2022.The recruitment will continue until the target population (78 nurses) is enrolled, which is expected to be ended in June 2023.And afterward, the data analysis will be implemented for publications.

Sample size
The aim of the cluster RCT is to improve the adherence to delirium intervention of ICU nurses by using the AI-AntiDelirium compared to the PADIS guideline.We expect that adherence to delirium intervention in the AI-Antidelirium group is 80% and PADIS guideline group is 50% 42 , suggesting that AI-Antidelirium has clinical significance in improving the adherence to delirium intervention of ICU nurses.
Sample size calculations showed that 12 nurses in each cluster will provide 80% power and a two-sided significance level (α) of 0.05, with an intracluster (within-unit) correlation of 0.002 43 .In addition, taking into account possible dropout rate of 10%, we plan to enroll 13 nurses in each ICU, the final sample size is 78 (13*6) nurses.

Recruitment
All recruitment will carry out by trained research staffs who will not involve in the intervention and blind to the nurses' group assignments.Researchers will screen nurses daily base on the inclusion and exclusion criteria.Written informed consent will be obtained from all eligible nurses.To retain more nurses, research staffs will explain the benefit for nurses if this study successfully implement.

Randomisation
The risk of between-group contamination is reduced by cluster randomisation, ICUs will be randomised 1:1 to receive either AI-AntiDelirium care or PADIS guideline.We plan to recruit 6 ICUs in two hospitals, and matching the types of ICU (considering the different types of ICU nursing process, workload and patients illness severity and other factors which will affect the nurses' adherence).The allocation sequence is based on computer-generated random numbers, which is performed by a statistician who is independent of data analyses and not involved in data collection.In order to ensure the allocation concealment, the statistician will inform the each ICUs' allocation code to the study coordinator.And then, the study coordinator will inform the ICU nurses about which group they are allocated.All eligible nurses are recruited until the sample size is enough.

Blinding
Investigators who will enroll participants are are not made aware of the randomisation list and patients are kept unaware of their assignment.But the nurses who implement strategies are not be possible to blind the allocation due to the nature of the intervention.Baseline data and endpoints measures will be collected by data collectors or outcome assessors who have no role in the intervention and blind to the allocations.

Data collection
As shown in types of ICUs (2 Surgical ICU [SICU], 2 Respiratory ICU [RICU] and 2 Cardiac ICU [CICU]) as well as the variety of the samples, and the promise of ICU staff to improve the quality of care in ICU delirium.A tertiary hospital is a 1000-bed university-affiliated teaching hospital, with 42 adult ICU beds in the 3 participating ICUs.B tertiary hospital has 730 beds and 3 eligible ICUs of 46 beds, which the annual admission rate is about 850 patients.They have fully implemented hospital

Figure 1
Figure 1 study design

Figure 1 .
Figure 1.Modules of Application A: ICU delirium assessment tools and results; B: risk factors assessment and predictive risk value; C: nursing care plan; D: nursing checklist

Table 1 ,
44ior to the study, uniform training will be delivered by research staff to data collectors.All study data are anonymized and treated confidentially.Informed consent will be obtained from all ICU nurses prior to study participation.After that, basic demographic data of ICU nurses are collected, including: age, gender, marital status, education background, departments where they worked, years of ICU experience, professional title, baseline CL and level of knowledge.Level of knowledge refers to the nurses' knowledge of ICU delirium assessment tools, risk factors, prevention and intervention acquired through learning, or clinical practice, and measured using the Questionnaire of ICU delirium knowledge.A 20-item multiple-choice knowledge questionnaire was newly developed, with content validity was 0.96, overall cronbach's α values of the questionnaire was 0.81444.The higher of the score, the higher knowledge regarding ICU delirium.During the study, CL and adherence to interventions of ICU nurses are recorded each day at the end of the shift.Data are stored on electronic file powered by a data manager.